A Systematic Examination of Adaptive Protocols in Hybrid 5G and LoRaWAN IoT Environments

Abstract

Background: IoT devices are widely used in numerous fields, requiring strong and effective communication solutions. 5G networks promise high data speeds and minimal latency, but they may need help to provide cost-effective, energy-efficient connections across large regions. However, Low Power Wide Area Networks (LPWAN) like LoRaWAN are efficient for low-power, long-range communications but suffer from data rate restrictions and network congestion in dense installations. Objective: This study investigates the feasibility and practicality of a hybrid 5G and LoRaWAN solution to increase IoT connection. It uses its complimentary capabilities to improve data throughput, energy efficiency, and cost-effectiveness. Methods: A prototype hybrid network using 5G and LoRaWAN technologies was tested and compared. The assessment approach included data throughput, latency, energy usage, and cost. The network combined low-power sensors and high-throughput IoT devices to simulate circumstances. Results: By dynamically choosing the best communication method depending on device needs and network state, the hybrid approach improved support for diverse IoT use cases. 5G handled high-speed, low-latency traffic, whereas LoRaWAN handled low-speed, delay-tolerant data. In addition, adaptive switching was used to optimize both network technologies. Conclusion: The hybrid strategy combining 5G and LoRaWAN effectively combines 5G's high data rates with LoRaWAN's energy and cost efficiency, creating a flexible and scalable IoT solution. Future studies will optimize the adaptive switching algorithm and investigate wide-scale applications to progress and maintain IoT connection paradigms.

Keywords

• 5g
• lorawan (low power wide area network)
• iot (internet of things)
• hybrid connectivity
• data throughput
• latency
• energy efficiency
• cost-effectiveness
• adaptive switching
• network congestion